Single-source dual-energy computed tomography can accurately predict UA and non-UA stone composition in vitro and in vivo. Substratification of non-UA stones of pure composition can be made in vitro and in vivo. In stones of mixed composition, the Zeff values reflect the dominant composition.
Institutional Review Board approval was obtained and informed consent was waived for this HIPAA-compliant study. The aim of this study was to retrospectively compare the accuracy of semiautomated maximum intensity projection (MIP) images created at a 16-section multidetector CT console with three-dimensional (3D)-workstation-generated images for the definition of renal donor anatomy, with intraoperative findings as a reference standard. In examining 40 renal donors (21 men and 19 women; age range, 24-56 years; mean age, 40.4 years), the sensitivity and accuracy for mapping donor anatomy by two readers were greater than 95%, interobserver agreement was excellent (kappa = 0.89-1.00). The 95% confidence interval for sensitivity was also calculated. Simple MIPs compared well with 3D-workstation images. MIPs from a predesigned protocol on the scanner console were generated more quickly than similar images from 3D workstations; postprocessing demands (eg, for renal donors) can be quickly fulfilled at the scanner console itself. The average time to generate simple MIPs at the console was 3.4 minutes (range, 1.7-4.4 minutes), and 22.3 minutes (range, 15-30 minutes) to create images at the 3D workstation.
One of the most recent technological advancements in computed tomography (CT) is the introduction of multi-slice CT (MSCT). The state-of-the-art MSCT contains 16 detector rows and is capable of acquiring 16 projections simultaneously. In this paper, we propose a reconstruction algorithm that makes use of nontraditional reconstruction planes and convolution weighting. To minimize the impact of interpolation on slice-sensitivityprofile (SSP), conjugate samples are used for the projection interpolation. We use multiple convex planes as the region of reconstruction. This allows the generated weighting function to be smooth and differentiable. In addition, we make use ofthe fact that projections collected from a subset ofdetector rows are sufficient to perform a complete reconstruction. A convolution function is applied to the weighting function ofeach subset to minimize the impact of cone beam effects. The convolution function is chosen so that optimal balance is achieved between image artifact, slice-sensitivity-profile (SSP), and noise. Extensive phantom and clinical studies have been conducted to validate our approach. Our study indicates that compared to other row-interpolation based reconstruction algorithms, a 30% SSP improvement can be achieved with the proposed approach. In addition, image artifact suppression achieved with the proposed approach is on par or slightly better than the existing reconstruction algorithms. Extensive clinical studies have shown that the 16-slice scanner in conjunction with this algorithm produces nearly isotropic spatial resolution and allows much improved diagnostic image quality.
Purpose: To quantify the dosimetric impact of CT metal artifacts on proton pencil‐beam scanning and passive scattering delivery. To develop a novel metal artifact reduction method to reduce artifacts in CT simulation images. Method and Materials: A tissue characterization phantom was scanned on a wide‐bore CT simulation scanner with and without metallic inserts. Original projection data was obtained for these scans. Images have been reconstructed with filtered back projection using both the original projection data and a version in which the projections through metal are restored with a 2‐dimensional interpolation method. A target volume (GTV) was defined in the center of the phantom. Dose errors were calculated by planning on the artifact‐affected images and calculating the dose on the ground truth images without artifacts. Results: Dose errors in the plan for passive scattering delivery mainly occurred around the edge of the GTV, caused by the range shift of the beams. The impact of metal artifacts on pencil‐beam scanning delivery is much greater; interplay between the pencil‐beams and local image artifacts results in dose errors of up to 18% inside the GTV. The dose errors in both plans could be reduced to 3% by applying the metal artifact reduction method to the CT data. Also, tissue structure that was originally hidden could largely be restored, which in patient plans can facilitate better delineation of the tumor and organs‐at‐risk. Conclusions: This work shows that metal artifacts in the CT simulation scan for proton pencil‐beam scanning delivery can result in significant under‐ and overdosage inside the GTV, which could lead to poor tumor control. A metal artifact reduction method has been developed and shown to reduce proton dose errors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.